AIMC Topic: Emergency Medicine
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Can AI outperform a junior resident? Comparison of deep neural network to first-year radiology residents for identification of pneumothorax.
Emergency radiology
Jul 8, 2020
PURPOSE: To (1) develop a deep learning system (DLS) using a deep convolutional neural network (DCNN) for identification of pneumothorax, (2) compare its performance to first-year radiology residents, and (3) evaluate the ability of a DLS to augment ...
Agents and robots for collaborating and supporting physicians in healthcare scenarios.
Journal of biomedical informatics
Jun 27, 2020
Monitoring patients through robotics telehealth systems is an interesting scenario where patients' conditions, and their environment, are dynamic and unknown variables. We propose to improve telehealth systems' features to include the ability to serv...
Usefulness of Machine Learning-Based Detection and Classification of Cardiac Arrhythmias With 12-Lead Electrocardiograms.
The Canadian journal of cardiology
Mar 5, 2020
BACKGROUND: Deep-learning algorithms to annotate electrocardiograms (ECGs) and classify different types of cardiac arrhythmias with the use of a single-lead ECG input data set have been developed. It remains to be determined whether these algorithms ...
Artificial Intelligence in Emergency Medicine: Surmountable Barriers With Revolutionary Potential.
Annals of emergency medicine
Feb 21, 2020
Daring to be wise: We are black boxes, and artificial intelligence will be the solution.
Emergency medicine Australasia : EMA
Jul 28, 2019
Emergency physicians seek wisdom through personal resilience, deliberate reasoning, clinical consensus and reflective practice. However, there is a limit to how useful psychological training, clinical guidelines and audit initiatives can be in the fa...
The Extended Supervised Learning Event (ESLE): Assessing Nontechnical Skills in Emergency Medicine Trainees in the Workplace.
Annals of emergency medicine
Jul 17, 2019
STUDY OBJECTIVE: The contribution of emergency medicine clinicians' nontechnical skills in providing safe, high-quality care in the emergency department (ED) is well known. In 2015, the UK Royal College of Emergency Medicine introduced explicit valid...
Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview.
The western journal of emergency medicine
Feb 14, 2019
Health informatics is a vital technology that holds great promise in the healthcare setting. We describe two prominent health informatics tools relevant to emergency care, as well as the historical background and the current state of informatics. We ...
A Review of Natural Language Processing in Medical Education.
The western journal of emergency medicine
Dec 12, 2018
Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical education...
Deep neural network improves fracture detection by clinicians.
Proceedings of the National Academy of Sciences of the United States of America
Oct 22, 2018
Suspected fractures are among the most common reasons for patients to visit emergency departments (EDs), and X-ray imaging is the primary diagnostic tool used by clinicians to assess patients for fractures. Missing a fracture in a radiograph often ha...
Validation of deep-learning-based triage and acuity score using a large national dataset.
PloS one
Oct 15, 2018
AIM: Triage is important in identifying high-risk patients amongst many less urgent patients as emergency department (ED) overcrowding has become a national crisis recently. This study aims to validate that a Deep-learning-based Triage and Acuity Sco...
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